The Political Economy of New Cleavages: Place-based Politics in the United States and Canada
Bibliographic record
Abstract
This dissertation examines how evolving economic geographies shape political cleavages in the United States and Canada. Through three papers, it analyses the political ramifications of place-based economic transformations. The first paper demonstrates that homeowners in high-cost urban areas oppose both redistributive policies and housing supply reforms. It reveals how geographically concentrated, knowledge-led growth creates new wealth divides, which in turn fuel political polarisation between homeowners and renters. The second paper investigates Canada’s energy transition, showing how the anticipated economic impact of decarbonisation generates electoral backlash in carbon-intensive regions, where local employment shocks drive opposition to the incumbent Liberal Party. The paper demonstrates how the energy transition is creating new place-based cleavages between regions whose economic fabric is heavily reliant on extractive industries and those whose growth is driven by low-carbon, service-based sectors. The third paper connects declining internal labour mobility to right-wing populism in the American context. It argues that workers in vulnerable sectors who face limited alternative employment opportunities at the regional level and high housing costs impeding relocation to thriving regions of the country increasingly turn toward right-wing populism. Collectively, these papers document how post-industrial economic restructuring, characterised by the geographic concentration of growth around major knowledge-driven hubs, fossil fuel phaseouts, and reduced geographic mobility all create durable place-based political divides that transcend traditional class-based coalitions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.019 | 0.008 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".